BACKGROUND: Hospitals are standard of care for acute illness, but hospitals can be unsafe, uncomfortable, and expensive. Providing substitutive hospital-level care in a patient’s home potentially reduces cost while maintaining or improving quality, safety, and patient experience, although evidence from randomized controlled trials in the US is lacking. OBJECTIVE: Determine if home hospital care reduces cost while maintaining quality, safety, and patient experience. MAIN MEASURES: Primary outcome was direct cost of the acute care episode. Secondary outcomes included utilization, 30-day cost, physical activity, and patient experience. KEY RESULTS: Nine patients were randomized to home, 11 to usual care. Median direct cost of the acute care episode for home patients was 52% (IQR, 28%; p = 0.05) lower than for control patients. During the care episode, home patients had fewer laboratory orders (median per admission: 6 vs. 19; p < 0.01) and less often received consultations (0% vs. 27%; p = 0.04). Home patients were more physically active (median minutes, 209 vs. 78; p < 0.01), with a trend toward more sleep. No adverse events occurred in home patients, one occurred in control patients. Median direct cost for the acute care plus 30-day post-discharge period for home patients was 67% (IQR, 77%; p < 0.01) lower, with trends toward less use of home-care services (22% vs. 55%; p = 0.08) and fewer readmissions (11% vs. 36%; p=0.32). Patient experience was similar in both groups. CONCLUSIONS: The use of substitutive home hospitalization compared to in-hospital usual care reduced cost and utilization and improved physical activity.

Continuous remote monitoring with convenient wireless sensors is attractive for early detection of patient deterioration, preventing adverse events and leading to better patient care. This article presents an innovative sensor design of VitalPatch, a fully disposable wireless biosensor, for remote continuous monitoring, and details the performance assessments from bench testing and laboratory validation in 57 subjects. The bench testing results reveal that VitalPatch's QRS detection had a positive predictive value of >99% from testing with ECG databases. The accuracies of HR, BR and skin temp (in mean absolute error, MAE) from bench testing were <;5 bpm, <;1 brpm, <; 1°C respectively. The laboratory testing in 57 subjects revealed the accuracy of HR and BR to be 2.2±1.5 bpm and 1.7±0.7 brpm respectively for stationary periods. The absolute percent error in detecting steps was 4.7±4.6%, and the accuracy in detecting posture was 96.4±3.1%. Meanwhile, the specificity and sensitivity of fall detection (n=20) was found to be 100% and 93.8%, respectively. In conclusion, VitalPatch biosensor demonstrated clinically acceptable accuracies for its vital signs and actigraphy metrics applicable for continuous unobtrusive patient monitoring.

Validation of biosensor algorithms is paramount for regulated medical devices applied to patient monitoring. We present validation of breathing rate (BR) measurement using a patch medical device via a novel synthetic simulation platform, in-hospital data collection and controlled laboratory study. Single-lead ECG and triaxial body acceleration signals with variability and noise are synthetically generated and quantized for a constellation according to the input parameters of heart rate (HR) as a fundamental frequency (f c ) of ECG and reference BR as a modulating frequency (f r ). Synthetic signals are input to the BR algorithms and the performance of output BRs are evaluated for a region-of-interest of the constellation (f c /f r ≥ 3 & f c /f r ≤ 8) accounting the Nyquist and physiological varability. The performances of patch sensor's BR are also evaluated in 13 post-operative patients with reference to a clinical bedside monitor and in 57 subjects carrying out a controlled laboratory protocol with reference to capnography. The synthetic simulations revealed mean absolute error (MAE) of 0.8±0.6 brpm and standard deviation of absolute error of 0.3±0.2 brpm for the BR algorithms of patch sensor. The controlled laboratory testing revealed MAE of 1.7±0.7 brpm (n=57) for stationary conditions. The proposed simulation platform can be useful for developmental refinement or validation of BR measurement prior to testing in humans at clinical or laboratory conditions and applicable for testing other patient monitoring devices with modular modifications.

Pulse arrival time (PAT) and pulse transit time (PTT) derived from the finger have been widely investigated for noninvasive blood pressure (BP) measurement. The study investigates the feasibility of BP measurement using a chest-worn patch sensor derived systolic timing intervals and pulse timing measurements. Healthy volunteers (N=14, 38 ± 13 years) carried out a protocol including deep breathing test, sustained hand grip test and modified Valsalva test with continuous physiological measurements from a patch sensor attached on left chest and intermittent BP measurements from an automated oscillometric monitor as a reference. The efficacy of chest derived PAT and PTT for univariate BP prediction is assessed using correlation and regression slope. The cross validation performance of predicting BP using multivariate regression model with chest derived systolic timing intervals and pulse timing features were also evaluated. The results suggest that the chest derived PAT and PTT had modest correlations (-0.52 and -0.31) and regression slopes (-0.21 and -0.14) with automated oscillometric systolic and diastolic BP references, respectively. On the other hand, a multivariate regression approach for prediction of mean blood pressure (MBP) using patch sensor measurements showed a correlation of 0.72, mean error of 0.1 mmHg and RMSE error of 5.1 mmHg compared to the oscillometric MBP values. The study demonstrated the feasibility of BP measurement using a wearable chest-worn patch sensor in healthy control subjects.

Sleep is a renowned marker of health. One in three adults endure sleep disorders without diagnosis due to lack of effective sleep screening technology. The study presents clinical validation of VitalPatch®, a wireless adhesive medical device for screening of sleep architecture in normal and apnea compared to the Polysomnography (PSG).

Tremendous interest prevails in developing a convenient and effective wearable medical device for evaluating sleep at home. The current study presents the clinical validation of VitalPatch®, a wireless adhesive patch sensor for screening of sleep architecture compared to the gold standard polysomnograph (PSG). A group of 45 volunteers were attached to a standard 22-channel PSG and a VitalPatch sensor on their chest. Simultaneous PSG and patch data were acquired overnight wirelessly. Hypnograms with wake, non-rapid eye movement (NREM), and REM stages were obtained using both the methods for a sequence of 30 s epochs corresponding to the bed-time, and the respective statistical sleep metrics were computed in 42 subjects. Performance, statistical and agreement analyses were conducted using VitalPatch’s sleep assessments compared to the PSG. The accuracy and Cohen’s kappa measures of 3-class sleep stage prediction (n=42) was 80.5±8.3% and 0.50±0.18, respectively. Total sleep time showed a strong linear correlation (r=0.88) with a mean absolute error (MAE) of 25 min compared to the PSG. NREM and REM sleep times were highly correlated to the PSG (r=0.82 and r=0.71, respectively) with MAE of 26 min and 16 min, respectively. The results suggest that unobtrusive disposable VitalPatch sensor is effective in predicting sleep architectures highly comparable to the PSG and can be useful for widespread screening of sleep patterns in home environment.

Development of wearable medical devices to measure noninvasive blood pressure (NIBP) has recently been evolving at finger/wrist and earlobe locations. The study investigates the predictive power of pulse transit time (PTT) and pulse arrival time (PAT) measured at finger and earlobe sites for BP measurement during two unique physiological interventions: handgrip test (HGT) and modified Valsalva test (mVT). Singlelead electrocardiogram, impedance cardiogram, infrared photoplethysmogram (PPG) from finger and earlobe, and CNAP® NIBP were simultaneously acquired in 14 healthy subjects (39±11 years); beat-to-beat BP, PAT and PTT were extracted; linear regression, correlation and statistical analyses were carried out. The results show that both the BP interventions caused significant increase (P<0.05) in diastolic blood pressure (DBP), but concurrent significant decrease (P<0.01) in PTT was observed only during mVT in both finger and earlobe sites. On the other hand, PAT did not change significantly during both the BP interventions. PTT showed highest correlation (R2) of 0.47±0.26 and negative regression slope of −0.39±0.31 with DBP in finger during mVT compared to earlobe. Thus, the predictive power of PTT for NIBP monitoring vary broadly in distinct BP regulation mechanisms, and found to be moderate in finger site and relatively weak in earlobe site.